Abstract
High-frequency disturbance forest ecosystems undergo complex and frequent changes at various spatiotemporal scales owing to natural and anthropogenic factors. Effectively capturing the characteristics of these spatiotemporal changes from satellite image time series is a powerful and practical means for determining their causes and predicting their trends. Herein, we combined the spatiotemporal cube and vegetation indices to develop the improved spatiotemporal cube (IST-cube) model. We used this to acquire the spatiotemporal dynamics of forest ecosystems from 1987 to 2020 in the study area and then classified it into four spatiotemporal scales. The results showed that the cube-core only exists in the increasing IST-cubes, which are distributed in residential areas and forests. The length of the IST-cube implies the duration of triggers. Human activities result in long-term small-scope IST-cubes, and the impact in the vicinity of residential areas is increasing while there is no change within. Meteorological disasters cause short-term, large scope, and irregular impacts. Land use type change causes short-term small scope IST-cubes and a regular impact. Overall, we report the robustness and strength of the IST-cube model in capturing spatiotemporal changes in forest ecosystems, providing a novel method to examine complex changes in forest ecosystems via remote sensing.
Highlights
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In terms of land use, approximately 84% of the land is occupied by forests; the rest is used for mining and comprises residential settlements, factories, agricultural farms, and roads
We introduced Palmer drought severity index (PDSI) as validation data to perform a quantitative evaluation on IST-cubes
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Forests are the habitat of numerous natural species and serve multiple economic functions for human society [1,2,3]. Conditions conducive to stable forest growth include the absence of disturbances which includes meteorological disasters, human activities, etc. High-frequency disturbances will likely produce more severe impact on forests
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